Redux Performance Profiling

Performance Profiling Overview

At its core, performance profiling is about doing one thing well in Redux. Once you understand the pattern, you can apply it consistently across projects and teams.

Good performance profiling pays off across the whole project: fewer surprises, easier collaboration, and smoother onboarding. The snippet below is a solid starting point.

import { configureStore } from '@reduxjs/toolkit';
import { Provider } from 'react-redux';

const store = configureStore({ reducer: rootReducer });

function App() {
  return (
    <Provider store={store}>
      <Root />
    </Provider>
  );
}

A Provider makes the single Redux store available to every component in the tree.

Performance Profiling Example

const slice = createSlice({ name, initialState, reducers });
const store = configureStore({ reducer: { key: slice.reducer } });
// dispatch(slice.actions.something())

• Start from a minimal Performance Profiling example and grow it only as needed.
• Keep things explicit so Performance Profiling behaves the same for everyone on the team.
• Name things clearly so teammates understand your Performance Profiling at a glance.
• Verify Performance Profiling works as expected before relying on it in important work.

Redux Cheatsheet

Quick Redux Toolkit reference related to performance profiling.

How Performance Profiling Works in Redux

Performance Profiling follows Redux's predictable data flow: components dispatch actions, reducers compute the next state from the previous state and the action, and subscribed components re-render.

A Provider makes the single Redux store available to every component in the tree.

• State lives in a single, read-only store.
• Actions are the only way to describe a change.
• Reducers are pure functions that return the next state.
• Redux Toolkit removes most boilerplate with slices and thunks.

Practical Guidance for Performance Profiling

In modern apps, performance profiling should use Redux Toolkit rather than hand-written Redux. Keep state minimal, colocate logic in slices, and use RTK Query for server data.

Common Mistakes

• Copying performance profiling commands or snippets without understanding what each part does.
• Skipping edge cases and error handling when using performance profiling.
• Not verifying the result of performance profiling before moving on.
• Over-complicating performance profiling before you actually need the extra flexibility.

Key Takeaways

• Performance Profiling is a core part of working effectively with Redux.
• Start small and keep performance profiling focused on a single goal.
• Apply consistent patterns so performance profiling scales across your project.
• Practise and document performance profiling to keep your workflow maintainable.